Top Analysis Reporting Jobs in Richmond, VA

Analyze business performance, develop hypotheses, answer critical business questions, and build dashboards and reports in Sigma. Support budgeting, forecasting, data quality checks, and reconciliations while partnering with teams across growth, product, insurance, finance, and leadership. Serve as a trusted data advisor by answering metric and reporting questions and promoting data-driven decision-making.

Own go-to-market funnel reporting, dashboards, data quality, and analysis for Sales, Marketing, and RevOps. Integrate CRM and marketing data, monitor lead scoring and attribution models, investigate funnel performance, identify root causes, and provide actionable recommendations. Maintain reporting systems, audit data hygiene and tool adoption, and communicate insights clearly to non-technical stakeholders in a remote-first SaaS environment.

Own experimentation analytics across Product and Marketing, including A/B and multivariate test design, causal inference, statistical analysis, and business recommendations. Build dbt models, dashboards, metrics, and experimentation frameworks; improve data infrastructure and self-service reporting; partner with engineering on instrumentation; mentor analysts; and maintain the analytics roadmap while supporting cross-functional stakeholders.

Short-term, paid project to export and submit personal financial data from multiple apps. Participants must provide exports from specific financial categories, create two financial artifacts, redact PII on-device using a provided tool, and follow quality and timeline requirements until Final Approval.

Design and build a durable data storage platform that preserves source disagreements, provenance, uncertainty, historical versions, and evidence. Develop result and evidence stores, lineage tracking, versioned rules and configurations, reproducible decision records, and point-in-time entity views. Collaborate with entity-resolution and machine-learning teams to support probabilistic outputs. The role requires production data engineering experience, strong Python and SQL, PostgreSQL expertise, U.S. citizenship, and an active Secret clearance.

Supports client projects by creating metadata, writing and testing R syntax, cleaning and recoding survey data, performing statistical operations, reviewing code and outputs, documenting data-management processes, and troubleshooting errors. The role requires independent task management, technical communication, quality control, and collaboration on federally contracted projects involving sensitive information.

Develop marketing budget allocation models, Early LTV metrics, performance diagnostic frameworks, and analytical tools. Analyze products, channels, campaigns, cohorts, attribution, and marketing economics using SQL, experimentation, BI tools, and spreadsheets. Support AI-based analytics development and unified BI metrics while translating findings into business rules and recommendations.

Own Carrum Health’s dbt data mart, semantic layer, client-facing exports, and data reliability standards. Lead, coach, and hire analytics engineers while establishing testing, documentation, freshness monitoring, metadata, and governance practices. Develop Hex as a trusted self-service analytics and AI interface with PHI controls, support the Databricks migration, and translate business needs into prioritized technical work. The role requires hands-on coding, strong dbt expertise, cloud data warehousing experience, and operational data ownership.

Designs and governs scalable dbt data architecture, analytics models, testing, documentation, metadata, and semantic-layer standards. Builds agent-safe infrastructure and self-service analytics experiences in Hex, improves data quality and reliability, and partners with engineering, data science, and business teams. The role also influences roadmap decisions, mentors teammates, and develops reusable tooling and frameworks for trusted, cost-efficient cloud data products.

Designs and implements scalable software solutions, develops maintainable features, resolves bugs, optimizes performance, and writes automated tests. Participates in architecture discussions, code reviews, Agile planning, CI/CD, observability, and adoption of AI-assisted engineering tools. Collaborates with QA, Product Management, and DevOps to deliver software across web, desktop, cloud, and IoT environments. The role is remote for candidates in the Seattle or Los Angeles metropolitan areas, with quarterly travel to Los Angeles.

Build and maintain analytics solutions for cloud technology and network infrastructure teams. Responsibilities include gathering requirements, automating reporting, developing self-service analytics, maintaining data pipelines and models, querying multiple data sources, and communicating insights through dashboards and reports. The role supports data-driven planning, capacity management, colocation, and finance decisions while collaborating with technical and business stakeholders.